Quickly and accurately estimating locations of things (e.g., receivers) in a geographic area can be used to speed up emergency response times, track business assets, and link consumers to nearby businesses. Various techniques are used to estimate the position of a thing in a geographic area. One such technique is trilateration, which is the process of using geometry to estimate the position of the thing using distances traveled by different signals that are transmitted from geographically-distributed transmitters and later received by that thing. Urban areas pose challenges that lengthen the time it takes to accurately estimate a thing's location. In an urban environment, the distances traveled by the different signals are longer than the actual distance between the thing and the transmitters that transmitted the different signals. These longer distances are the consequence of each signal reflecting off of buildings that are located between the thing and the transmitters, which creates a signal pathway that consists of multiple paths between consecutive reflections. Unfortunately, the longer distances caused by these “multipath” reflections cause result in less accurate estimates of the thing's position and/or longer periods of time during which a sufficiently-accurate estimate of the thing's position is computed. Accordingly, there is a need for improved techniques for mitigating the effects of multipath reflections on achieving timely and sufficiently-accurate estimates of a receiver's position.